| def seed_everything(seed=1234): | |
| random.seed(seed) | |
| os.environ['PYTHONHASHSEED'] = str(seed) | |
| np.random.seed(seed) | |
| tensorflow.random.set_seed(seed) | |
| tensorflow.keras.layers.Dropout(x, seed=SEED) | |
| tensorflow.image.random_flip_left_right(x, seed=seed) | |
| tensorflow.random_normal_initializer(x, y, seed=seed) | |
| # call this function a the beginning of your script |
| # Author: HJ van Veen <info@mlwave.com> | |
| # Description: Experiment to learn a tSNE transformer for new | |
| # test data with a multi-output GBM | |
| # | |
| # Idea first seen at lvdmaaten.github.io/tsne | |
| # > [...] it is not possible to embed test points in an existing | |
| # > map [...] | |
| # > A potential approach to deal with this would be to train | |
| # > a multivariate regressor to predict the map location from | |
| # > the input data. |
| transforms = [] | |
| transforms.append( | |
| ('select_binary', ColumnSelector(features=binary)) | |
| ) | |
| transforms.append( | |
| ('numeric', ExtendedPipeline([ | |
| ('select', ColumnSelector(features=numeric)), | |
| ('impute', Imputer(missing_values='NaN', strategy='mean', axis=0)), |
People
 :bowtie: |
😄 :smile: |
😆 :laughing: |
|---|---|---|
😊 :blush: |
😃 :smiley: |
:relaxed: |
😏 :smirk: |
😍 :heart_eyes: |
😘 :kissing_heart: |
😚 :kissing_closed_eyes: |
😳 :flushed: |
😌 :relieved: |
😆 :satisfied: |
😁 :grin: |
😉 :wink: |
😜 :stuck_out_tongue_winking_eye: |
😝 :stuck_out_tongue_closed_eyes: |
😀 :grinning: |
😗 :kissing: |
😙 :kissing_smiling_eyes: |
😛 :stuck_out_tongue: |
| #!/usr/bin/env python | |
| ''' | |
| Simple test script to see if we get ValueErrors with joblib and the current | |
| version of Python | |
| ''' | |
| import logging | |
| import sys | |
| from multiprocessing import cpu_count | |
| import sklearn.datasets |
| {"error": 42716.2954, "samples": 506, "value": [22.532806324110698], "label": "RM <= 6.94", "type": "split", "children": [{"error": 17317.3210, "samples": 430, "value": [19.93372093023257], "label": "LSTAT <= 14.40", "type": "split", "children": [{"error": 6632.2175, "samples": 255, "value": [23.349803921568636], "label": "DIS <= 1.38", "type": "split", "children": [{"error": 390.7280, "samples": 5, "value": [45.58], "label": "CRIM <= 10.59", "type": "split", "children": [{"error": 0.0000, "samples": 4, "value": [50.0], "label": "Leaf - 4", "type": "leaf"}, {"error": 0.0000, "samples": 1, "value": [27.9], "label": "Leaf - 5", "type": "leaf"}]}, {"error": 3721.1632, "samples": 250, "value": [22.90520000000001], "label": "RM <= 6.54", "type": "split", "children": [{"error": 1636.0675, "samples": 195, "value": [21.629743589743576], "label": "LSTAT <= 7.57", "type": "split", "children": [{"error": 129.6307, "samples": 43, "value": [23.969767441860473], "label": "TAX <= 222.50", "type": "split", "children": [{"err |
